Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

Cognitive Radio Networks allow unlicensed users to opportunistically access the licensed spectrum without causing disruptive interference to the Primary Users (PUs). One of the main challenges in CRNs is the ability to detect PU transmissions. Recent works have suggested the use of Secondary User (SU) cooperation over individual sensing to improve sensing accuracy. In this paper, the authors consider a CRN consisting of a single PU and multiple SUs to study the problem of maximizing the total expected system throughput. They propose a Bayesian decision rule based algorithm to solve the problem optimally with a constant time complexity. To prioritize PU transmissions, they re-formulate the throughput maximization problem by adding a constraint on the PU throughput.